Summary: Opponent Modeling in Scrabble
Mark Richards and Eyal Amir
Computer Science Department
University of Illinois at Urbana-Champaign
{ mdrichar,eyal } @cs.uiuc.edu
Abstract
Computers have already eclipsed the level of hu-
man play in competitive Scrabble, but there re-
mains room for improvement. In particular, there
is much to be gained by incorporating information
about the opponent's tiles into the decision-making
process. In this work, we quantify the value of
knowing what letters the opponent has. We use
observations from previous plays to predict what
tiles our opponent may hold and then use this infor-
mation to guide our play. Our model of the oppo-
nent, based on Bayes' theorem, sacrifices accuracy
for simplicity and ease of computation. But even
with this simplified model, we show significant im-
provement in play over an existing Scrabble pro-